data warehousing & business intelligence€¦ · data warehousing & business intelligence...
TRANSCRIPT
Rick van der Lans
Lex Pierik
Rutger Rienks
Nigel Turner
Keith McCormick
Martin Kersten
Lawrence Corr
Kent Graziano
MARCH 27-28, 2019UTRECHT
DATA WAREHOUSING & BUSINESS INTELLIGENCE SUMMIT 2019Big Data, Agile Datawarehouse Design, Analytics & Data Science, Dimensional Modeling, Data Storytelling, Cloud-based BI
■■ Increasing the success of BI projects through data-driven storytelling
■■ The influence of new database technology on data architectures
■■ Data warehouses: now and in the future; the influence of cloud
■■ Dimensional data modeling using the technique Data Model Storming
■■ Dealing with organizational resistance to predictive analytics
■■ Why is the marriage between data warehousing and data quality still not perfect?
■■ Setting up a successful data strategy that fits the business strategy
■■ How can we design data warehouses faster with agile design methods?
■■ The new world of Business Intelligence: from batch to Lambda and to Kappa
Acclaimed speakers
Kent Graziano, Keith McCormick, Lawrence Corr, Nigel Turner, Martin Kersten, Rutger Rienks, Lex Pierik and Rick van der Lans
Follow us @AdeptEventsNLEvent hash tag: #dwbisummit
WORKSHOP APRIL 1 - 2, 2019Keith McCormick will host a practical hands-on workshop
PUTTING MACHINE LEARNING TO WORKTranslating Organizational Challenges into Supervised & Unsupervised Learning Solutions
INFORMATION AND REGISTRATION: WWW.DWBISUMMIT.COM
DATA WAREHOUSING & BUSINESS INTELLIGENCE SUMMIT 2019The data-driven organization and digital transformation are key topics in the IT industry and in the board rooms. Sometimes these concepts are over-simplified, as if a simple action is sufficient to transform an organization into a data-driven one. Nothing is further from the truth. Although many organizations have their own definition of what they mean with the two concepts, they all do agree on that both concepts are essential and that data must play a greater role in business operations. Data must be used more intensively within an organization, for example by means of data science, the yield from the current investment in data can be increased, data must be used more widely in numerous business areas, and AI techniques must be deployed to discover new business insights.Indirectly, the sixth edition of the DW&BI Summit is focused on this increasing need for data-driven organizations and their digital transformation. Organizational, technical, and architectural aspects are explained. Topics include dealing with the resistance to technological innovations, what database technology will look like in five years’ time, the importance of storytelling, and the design of future-proof data architectures.The conference offers practical guidelines and do’s and don’ts to help you with these current and impending issues. You will meet well-known speakers and thought leaders from the Netherlands and abroad, including Keith McCormick, Lawrence Corr, Kent Graziano, Nigel Turner, Martin Kersten and Rick van der Lans.Once again, we managed to set up a very strong line-up with internationally acclaimed speakers, ready to share their knowledge and experience with you.
Some of the main topics that will be discussed these two days:• Increasing the success of BI projects through data-driven
storytelling• The influence of new database technology on data
architectures• Data warehouses: now and in the future; the influence of
cloud• Transforming business models into dimensional data
models using the technique Data Model Storming
• Dealing with organizational resistance to predictive analytics
• Why is the marriage between data warehousing and data quality still not perfect?
• Setting up a successful data strategy that fits the business strategy
• How can we design data warehouses faster with agile design methods?
• The new world of Business Intelligence: from batch to Lambda and to Kappa.
Who should attendThe two day DW&BI Summit is geared to for IT Executives, IT Management and Architects, business intelligence and data warehousing professionals who wish to take a detailed and practical look at the latest developments in Data Warehousing and Business Intelligence. The following professionals should attend:• Sponsors of BI and DW programs• Business technology managers• IT executives and managers• BI/DW project managers• Data warehousing architects• Business intelligence practitioners• Business analysts• Data scientists• Technology architects• Data architects and data modelers• Project and program managers• Data integrators• Developers of BI and DW systems• Business and IT consultants
Limited time? Join us one dayCan you only attend one day? It is possible to attend only the first or only the second conference day and of course the full conference. The presentations by our speakers have been selected in such a way that they can stand on their own. This enables you to attend the second conference day even if you did not attend the first (or the other way around).
This is the sixth edition of DW&BI Summit in The Netherlands. This upcoming edition you can benefit from the expertise of Keith McCormick, Lawrence Corr, Kent Graziano, Nigel Turner, Martin Kersten and Rick van der Lans amongst others. Each year will see key note presentations by the crème de la crème of the international data warehouse and BI community. Internationally acclaimed speakers like Bill Inmon, Claudia Imhoff, Donald Farmer, Nigel Pendse, Colin White, Mike Ferguson, Wayne Eckerson, Mark Madsen, William McKnight, Richard Hackathorn, John Ladley, Dan Linstedt, Barry Devlin, Krish Krishnan, Daragh O Brien and Jan Henderyckx have graced earlier editions of this conference with their presence.
KEITH MCCORMICK is a highly
accomplished professional senior
consultant, mentor, and trainer, having
served as keynote and moderator at
international conferences focused on
analytic practitioners and leadership alike. Keith has
leveraged statistical software since 1990 along with deep
expertise utilizing popular industry advanced analytics
solutions such as IBM SPSS Statistics, IBM SPSS Modeler,
AMOS, Answer Tree, popular open source and other tools
involving text and big data analytics. Keith McCormick has
guided organizations to establish highly effective analytical
practices across industries, to include public sector, media,
marketing, healthcare, retail, finance, manufacturing and
higher education. He holds a very unique blend of tactical
and strategic skill along with the business acumen to ensure
superior project design, oversight and outcomes that align
with organizational targets.
RICK VAN DER LANS is a highly-
respected independent analyst, consultant,
author, and internationally acclaimed
lecturer specializing in data warehousing,
business intelligence, big data, and
database technology.
He has presented countless seminars, webinars, and
keynotes at industry-leading conferences. For many years,
he has served as the chairman of the annual European
Enterprise Data and Business Intelligence Conference in
London and the annual Data Warehousing and Business
Intelligence Summit in The Netherlands. Rick helps clients
worldwide to design their data warehouse, big data, and
business intelligence architectures and solutions and assists
them with selecting the right products. He has been
influential in introducing the new logical data warehouse
architecture worldwide which helps organizations to
develop more agile business intelligence systems. Over the
years, Rick has written hundreds of articles and blogs for
newspapers and websites and has authored many
educational and popular white papers for a long list of
vendors. He was the author of the first available book on
INTERNATIONALLY ACCLAIMED SPEAKERSSQL, entitled including Introduction to SQL, which has been
translated into several languages with more than 100,000
copies sold. More recently, he published his book Data
Virtualization for Business Intelligence Systems. In 2018
Rick ranked sixth place as most influential BI-analist
worldwide on the Onalytica Influencer List.
LAWRENCE CORR is a leading
international BI consultant and former
Ralph Kimball Associate. He is the author of
Agile Data Warehouse Design: Collaborative
Dimensional Modeling, from Whiteboard to
Star Schema, an Amazon #1 bestseller in data warehousing
and database design. Lawrence has worked on data
warehousing projects in the US, Europe, the Middle East and
Africa within healthcare, telecoms, broadcasting, higher
education, financial services and retail, helping
organizations benefit from simpler, more inclusive
requirements modeling techniques. Lawrence’s new book
Data Modelstorming: Using BEAM to Design the Data
Everyone Wants will be published in 2019.
NIGEL TURNER is Principal Information
Management Consultant for EMEA at Global
Data Strategy Ltd. and Vice-Chair of the
Data Management Association of the UK.
Nigel has worked in Information
Management for over 25 years, both as an in-house deliverer
of Information Management solutions at British
Telecommunications plc and subsequently as an external
consultant to more than 150 clients, including British Gas,
UK Environment Agency, Intel US and others. He also works
as a part time project manager at Cardiff University’s
National Software Academy. Nigel is a sought after speaker
at conferences on information management and is based in
Cardiff, UK.
KENT GRAZIANO is the Chief Technical
Evangelist for Snowflake Computing. He is
an award winning author, speaker, and
trainer, in the areas of data modeling, data
architecture, and data warehousing. He is
an Oracle ACE Director – Alumni, member of the OakTable
Network, a certified Data Vault Master and Data Vault 2.0
Practitioner (CDVP2), expert data modeler and solution
architect with more than 30 years of experience, including
over two decades doing data warehousing and business
intelligence (in multiple industries). He is an internationally
recognized expert in Data Vault and Agile Data Warehousing.
Mr. Graziano has developed and led many successful
software and data warehouse implementation teams,
including multiple agile DW/BI teams. He has written
numerous articles, authored three Kindle book (available on
Amazon.com), co-authored four books (including the 1st
Edition of The Data Model Resource Book), and has given
hundreds of presentations, nationally and internationally.
He was a co-author on the first book on Data Vault, and the
technical editor for Super Charge Your Data Warehouse. In
2014, he was voted one of the best presenters at OUGF14
in Helsinki, Finland. You can follow Kent on twitter
@ KentGraziano or on his blog The Data Warrior
(http://kentgraziano.com).
MARTIN KERSTEN is a computer scientist
with research focus on database
architectures, query optimization and their
use in scientific databases. He is an
architect of the MonetDB system, an open-
source column store database for data warehouses, online
analytical processing (OLAP) and geographic information
systems (GIS). For this work he received the prestigious ACM
SIGMOD E.F. Codd Innovation Award and the ACM SIGMOD
Systems Award. He published more than 150 papers and is
an ACM Research Fellow. He has been (co-) founder of
several successful spin-offs of CWI such as Data Distilleries
and MonetDB.
LEX PIERIK started working in the ICT
industry in 2000 and by extensive field
experiences he quickly grew into his
current role as a principal BI consultant. He
is a seasoned ICT professional with a
particular expertise in both the conceptual as well as the
technical complexities of BI challenges. Lex is the creator
and facilitator of tool agnostic visualization training sessions
and he has been able to convince many companies and both
BI and non-BI professionals of the importance of
visualization techniques in order to produce actionable
insights.
RUTGER RIENKS is the author of
“Predictive Policing: Taking a Chance for a
Safer Future”. He holds a PhD in computer
science from the University of Twente in
The Netherlands and is a well-known
enthusiastic speaker.Rutger has broad experience in
Business Intelligence and Predictive Analytics. To broaden
his view he exchanged the Dutch National Police after eight
years for the City of Amsterdam in order to contribute in the
transformation of Amsterdam becoming a smart city.
Currently Rutger is employed as Thought Leader Data
Strategy at KPN. He was one of the speakers at a previous
edition of our yearly conference, the Data Warehousing &
Business Intelligence Summit.
WEDNESDAY, MARCH 27
Session 1The influence of the new technologies on data architectures – Rick van der Lans
Session 2AData Modelstorming: From Business Models to Analytical
Models – Lawrence Corr
Session 2BHet moderne database eco-systeem in een snel veranderde
wereld – Martin Kersten
Session 3ABecoming Data Driven – A Data Strategy for Success &
Business Insight – Nigel Turner
Session 3BModel Deployment for Production & Adoption – Why the
Last Task Should be the First Discussed – Keith McCormick
Session 4Agile Methods and Data Warehousing: How to Deliver Faster – Kent Graziano
THURSDAY, MARCH 28
Session 5Addressing Organizational Resistance to Predictive Analytics and Machine Learning – Keith McCormick
Session 6AData Warehousing in Today and Beyond – Kent Graziano
Session 6BMaak uw BI-project succesvol met Data-Driven Storytelling
– Lex Pierik
Session 7AData Quality & BI/DW – Not yet a marriage made in heaven
– Nigel Turner
Session 7BDe nieuwe business intelligence wereld: van Batch naar
Lambda en Kappa – Rutger Rienks
Session 8Developing your own Enterprise Data Marketplace – Rick van der Lans
Daily schedule:09:30 – 09:45 Opening by Conference Chairman
09:45 – 11:00 Session 1
11:00 – 11:15 Coffee break
11:15 – 11:45 Case study
11:45 – 13:00 Session 2A en Session 2B
13:00 – 14:00 Lunch
14:00 – 15:15 Session 3A en Session 3B
15:15 – 15:30 Coffee break
15:30 – 16:00 Case study
16:00 – 17:15 Session 4
On the 27th of March, there will be a reception after the final
session
CONFERENCE OUTLINE
Download the DW&BI Summit Conference-App (integrated in the BI-Platform app)
CONFERENCE-APP
The programme starts at 9:30 am and ends at 5:15 pm on both conference days. Registration commences at 8.30 am.
1. The influence of the new technologies on data architectures (Dutch spoken)
Rick van der Lans, Managing Director, R20/Consultancy
The rules used to be that data architectures had to be
designed independently of the technologies and products;
first, design the data architecture and then select the right
products. This was achievable because many products were
reasonably interchangeable. But is that still possible? In
recent years we have been confronted with an unremitting
stream of technologies for processing, analyzing and storing
data, such as Hadoop, NoSQL, NewSQL, GPU-databases,
Spark and Kafka. These technologies have a major impact
on data processing architectures, such as data warehouses
and streaming applications. But most importantly, many of
these products have very unique internal architectures and
directly enforce certain data architectures. So, can we still
develop a technology independent data architecture? In this
session the potential influence of the new technologies on
data architectures is explained.
• Are we stuck in our old ideas about data architecture?
• From generic to specialized technologies
• Examples of technologies that enforce a certain data
architecture
• What is the role of software generators in this discussion?
• New technology can only be used optimally if the data
architecture is geared to it.
2A. Data Modelstorming: From Business Models to Analytical ModelsLawrence Corr, Chief Data Modelstormer, DecisionOne Consulting
Have you ever been disappointed with the results of
traditional data requirements gathering, especially for BI
and data analytics? Ever wished you could ‘cut to the chase’
and somehow model the data directly with the people who
know it and want to use it. However, that’s not a realistic
alternative, is it? Business people don’t do data modeling!
But what if that wasn’t the case?
In this lively session Lawrence Corr shares his favourite
collaborative modeling techniques – popularized in books
such as ‘Business Model Generation’ and ‘Agile Data
Warehouse Design’ – for successfully engaging stakeholders
using BEAM (Business Event Analysis and Modeling) and the
Business Model Canvas for value-driven BI requirements
gathering and star schema design. Learn how visual thinking,
narrative, 7Ws and lots of Post-it™ notes can get your
stakeholders thinking dimensionally and capturing their own
data requirements with agility.
This session will cover:
• The whys of data modelstorming: Why it’s different from
traditional data modeling and why we need it
• Drawing user-focused data models: alternatives to entity
relation diagrams for visualising data opportunities
• Using BEAM (Business Event Analysis and Modeling) to
discover key data sources and define rich data sets
• How making toast can encourage collaborative modeling
within your organisation
• Modelstorming templates which you can download and
start using straight away.
2B. Het moderne database eco-systeem in een snel veranderende wereld (Dutch spoken)
Martin Kersten, Computer Scientist, Centrum Wiskunde & Informatica
Cloud diensten, in-memory databases en database servers
die gebruik maken van massive parallel processing voeren
de boventoon in de marketing hype van vandaag. Maar
wat is er de laatste tien jaar nu echt veranderd in de
databasemarkt? Welke aanbieders zijn in staat om vooruit
te blijven lopen op technologisch gebied? Moeten we ons
zorgen maken over de invloed van nieuwe hardware zoals
GPU en non-volatile memory? En kunnen we wel vertrouwen
op programmeurs om keer op keer het wiel opnieuw uit
te vinden voor elke database-interactie? Wat zijn de hot
technologies in de labs van de database leveranciers?
In deze sessie zal vooral worden gekeken naar:
• Column stores, een de-facto standaard voor Business
Intelligence, met haar oorsprong in Nederland
• Van Hadoop tot Apache Spark, wanneer u wel en wanneer
u niet de portemonnee moet trekken
• Het slechten van de muren tussen het DBMS en
programmeertalen als Java/C/..
• Performance, niet alleen een kwestie van een benchmark
score
• Efficiënt omgaan met resources om geld te besparen.
3A. Becoming Data Driven – A Data Strategy for Success & Business InsightNigel Turner, Principal Information Management Consultant, Global Data Strategy
More enterprises are seeking to transform themselves
into data-driven, digitally based organisations. Many have
recognised that this will not be solely achieved by acquiring
new technologies and tools. Instead they are aware that
becoming data-driven requires a holistic transformation of
existing business models, involving culture change, process
redesign and re-engineering, and a step change in data
management capabilities.
To deliver this holistic transformation, creating and
delivering a coherent and overarching data strategy is
essential. Becoming data-driven requires a plan which
spells out what an organisation must do to achieve its data
transformational goals. A data strategy can be critical in
answering questions such as: How ready are we to become
data-driven? What data do we need to focus on, now and
in the future? What problems and opportunities should we
tackle first and why? What part does business intelligence
and data warehousing have to play in a data strategy?
How do we assess a data strategy’s success?
This session will outline how to produce a data strategy and
supporting roadmap, and how to ensure that it becomes a
living and agile blueprint for change rather than a statement
of aspiration.
This session will cover:
• The relationship between an organisation’s business
strategy and data strategy
• What a data strategy is (and is not)
• Building & delivering a data strategy – the key
components and steps
• The role of BI/DW in a data strategy – data issues and data
needs
• The ‘limit or liberate’ data dilemma and how to resolve it
through data governance
• Several use cases of successful data strategies and
lessons learned.
3B. Model Deployment for Production & Adoption – Why the Last Task Should be the First DiscussedKeith McCormick, Senior Consultant, The Modeling Agency
Most analytic modelers wait until after they’ve built a
model to consider deployment. Doing so practically ensures
project failure. Their motivations are typically sincere but
misplaced. In many cases, analysts want to first ensure that
there is something worth deploying. However, there are
very specific design issues that must be resolved before
meaningful data exploration, data preparation and modeling
can begin. The most obvious of many considerations to
address ahead of modeling is whether senior management
truly desires a deployed model. Perhaps the perceived
purpose of the model is insight and not deployment at
all. There is a myth that a model that manages to provide
insight will also have the characteristics desirable in a
deployed model. It is simply not true. No one benefits from
this lack of foresight and communication. This session will
convey imperative preparatory considerations to arrive at
accountable, deployable and adoptable projects and Keith
will share carefully chosen project design case studies and
how deployment is a critical design consideration.
• Which modeling approach continues to be the most
common and important in machine learning
• The iterative process from exploration to modeling to
deployment
• Which team members should be consulted in the earliest
stages of predictive analytics project design?
• Misconceptions about predictive analytics, modeling, and
deployment
• Costly strategic design errors to avoid in predictive
analytics projects
• Common styles of deployment.
4. Agile Methods and Data Warehousing: How to Deliver FasterKent Graziano, Chief Technical Evangelist, Snowflake
Most people will agree that data warehousing and
business intelligence projects take too long to deliver
tangible results. Often by the time a solution is in place,
the business needs have changed. With all the talk about
Agile development methods like SCRUM and Extreme
Programming, the question arises as to how these
approaches can be used to deliver data warehouse and
business intelligence projects faster. This presentation
will look at the 12 principles behind the Agile Manifesto
and see how they might be applied in the context of a data
warehouse project. The goal is to determine a method or
methods to get a more rapid (2-4 weeks) delivery of portions
of an enterprise data warehouse architecture.
Real world examples with metrics will be discussed.
• What are the original 12 principles of Agile
• How can they be applied to DW/BI projects
• Real world examples of successful application of the
principles.
5. Addressing Organizational Resistance to Predictive Analytics and Machine LearningKeith McCormick, Senior Consultant, The Modeling Agency
Many who work within organizations that are in the early
stages of their digital transformation are surprised when an
accurate model -- built with good intentions and capable of
producing measurable benefit to the organization -- faces
organizational resistance. No veteran modeler is surprised by
this because all projects face some organizational resistance
to some degree. This predictable and eminently manageable
problem simply requires attention during the project’s design
phase. Proper design will minimize resistance and most
projects will proceed to their natural conclusion – deployed
models that provide measurable and purposeful benefit to the
organization. Keith will share carefully chosen case studies
based upon real world projects that reveal why organizational
resistance was a problem and how it was addressed.
• Typical reasons why organizational resistance arises.
• Identifying and prioritizing valid opportunities that align
with organizational priorities
• Which teams members should be consulted early in the
project design to avoid resistance
• How to estimate ROI during the design phases and
achieve ROI in the validation phase
• The importance of a ‘dress rehearsal’ prior to going live.
6A. Data Warehousing in Today and BeyondKent Graziano, Chief Technical Evangelist, Snowflake
The world of data warehousing has changed! With the
advent of Big Data, Streaming Data, IoT, and The Cloud, what
is a modern data management professional to do? It may
seem to be a very different world with different concepts,
terms, and techniques. Or is it? Lots of people still talk about
having a data warehouse or several data marts across their
organization. But what does that really mean today? How
about the Corporate Information Factory (CIF), the Data
Vault, an Operational Data Store (ODS), or just star schemas?
Where do they fit now (or do they)? And now we have the
Extended Data Warehouse (XDW) as well. How do all these
things help us bring value and data-based decisions to
our organizations? Where do Big Data and the Cloud fit? Is
there a coherent architecture we can define? This talk will
endeavor to cut through the hype and the buzzword bingo
to help you figure out what part of this is helpful. I will
discuss what I have seen in the real world (working and not
working!) and a bit of where I think we are going and need to
go in today and beyond.
• What are the traditional/historical approaches
• What have organizations been doing recently
• What are the new options and some of their benefits.
6B. Maak uw BI-project succesvol met Data-Driven Storytelling (Dutch spoken)
Lex Pierik, Managing Director, Think.Design.Make
Al jaren bestaat de wereld van Business Intelligence (BI)
uit het bouwen van rapporten en dashboards. De BI-wereld
om ons heen verandert echter snel. (Statistical) Analytics
worden meer en meer ingezet, elke student krijgt gedegen
R-training en het gebruik van data verplaatst zich van IT
naar business. Maar zijn we wel klaar voor deze nieuwe
werkwijze? Zijn we in staat om de nieuw verkregen inzichten
te delen? En kunnen we echt het onderbuikgevoel van het
management veranderen?
Tijdens deze presentatie gaan we in op deze veranderende
wereld. We gaan in op hoe we het data-driven storytelling
proces kunnen toepassen binnen BI-projecten, welke
rollen zijn hiervoor nodig en u krijgt handvatten om nieuw
verkregen inzichten te communiceren via storytelling.
• Inzicht in het Data-driven storytelling process
• Visuele data exploratie
• Organisatorische wijzigingen
• Communiceren via Infographics
• Combineren van data, visualisatie en een verhaal.
7A. Data Quality & BI/DW – Not yet a marriage made in heavenNigel Turner, Principal Information Management Consultant, Global Data Strategy
The close links between data quality and business
intelligence & data warehousing (BI/DW) have long
been recognised. Their relationship is symbiotic. Robust
data quality is a keystone for successful BI/DW; BI/DW
can highlight data shortcomings and drive the need for
better data quality. A key driver for the invention of data
warehouses was that they would improve the integrity of the
data they store and process.
Despite this close bond between these data disciplines, their
marriage has not always been a successful one. Our industry
is littered with failed BI/DW projects, with an inability to
tackle and resolve underlying data quality issues often cited
as a primary reason for failure. Today many analytics and
data science projects are also failing to meet their goals for
the same reason.
Why has the history of BI/DW been plagued with an inability
to build and sustain the solid data quality foundation it
needs? This presentation tackles these issues and suggests
how BI/DW and data quality can and must support each other.
The Ancient Greeks understood this. We must do the same.
This session will address:
• What is data quality and why is it the core of effective
data management?
• What can happen when it goes wrong – business and
BI/DW implications
• The synergies between data quality and BI/DW
• Traditional approaches to tackling data quality for DW/BI
• The shortcomings of these approaches in today’s BI/DW
world
• New approaches for tackling today’s data quality
challenges
• Several use cases of organisations who have successfully
tackled data quality & the key lessons learned.
7B. De nieuwe business intelligence wereld: van Batch naar Lambda en Kappa (Dutch spoken)
Rutger Rienks, Though Leader Data Strategy, KPN
Met de komst van cloud computing is het mogelijk geworden
om data sneller te verwerken en infrastructuur mee te
laten schalen met de benodigde opslag en cpu capaciteit.
Waar voorheen batch computing de norm was en grote
datawarehouses werden ontwikkeld, zien we een transitie
naar data lakes en real-time verwerking. Eerst kwam de
lambda architectuur die naast de batch processing een
streaming processing layer toevoegde. En sinds 2014 zien
we dat de kappa architectuur de batch processing layer uit
de lambda architectuur helemaal weglaat.
Deze presentatie gaat in op Kappa architecturen. Wat zijn
de voor- en nadelen van het verwerken van data langs deze
architectuur ten opzichte van de oude batch verwerking
of de tussentijdse lambda architectuur? Dit vraagstuk zal
worden behandeld aan de hand van ervaringen bij KPN met
een product gebaseerd op een Kappa architectuur: de Data
Services Hub.
Centraal bij de beantwoording staan de aspecten die
tegenwoordig worden toebedeeld aan innovatieve
technologieën: homogenisatie en ontkoppeling,
modulariteit, connectiviteit, programmeerbaarheid en het
kunnen profiteren van ‘gebruikers’ sporen.
• Creëren van informatie en kennis uit data
• Hoe verhouden dashboarding en machine-learning in een
streaming context zich ten opzichte van de oude meer
bekende batch processing way of working?
• Wat betekenen MQTT, Pulsar, Spark en Flink?
• De waarde van centrale pub-sub message bussen, zoals
Kafka of Rabbit MQ.
8. Developing your own Enterprise Data Marketplace (Dutch spoken)
Rick van der Lans, Managing Director, R20/Consultancy
We have known public data marketplaces for a long
time. These are environments that provide all kinds of
data products that can be purchased or used. In recent
years, organizations have started to develop their own
data marketplace: the enterprise data marketplace. An
EDM is developed by its own organization and supplies
data products to internal and external data consumers.
Examples of data products are reports, data services, data
streams, batch files, etcetera. The essential difference
between an enterprise data warehouse and an enterprise
data marketplace is that with the former users are asked
what they need and with the latter it is assumed that the
marketplace owners know what the users need. Or in other
words, we go from demand-driven to supply-driven. This all
sounds easy, but it isn’t at all. In this session, the challenges
of developing your own enterprise data marketplace are
discussed.
• Challenges: research, development, marketing, selling,
payment method
• Is special technology needed for developing a data
marketplace?
• Differences between data warehouses and marketplaces
• Including a data marketplace in a unified data fabric
• The importance of a searchable data catalog.
Supervised learning solves modern analytics challenges
and drives informed organizational decisions. Although the
predictive power of machine learning models can be very
impressive, there is no benefit unless they inform value-
focused actions. Models must be deployed in an automated
fashion to continually support decision making for residual
impact. And while unsupervised methods open powerful
analytic opportunities, they do not come with a clear path
to deployment. This course will clarify when each approach
best fits the business need and show you how to derive
value from both approaches.
Regression, decision trees, neural networks – along with
many other supervised learning techniques - provide
powerful predictive insights when historical outcome data is
available. Once built, supervised learning models produce a
propensity score which can be used to support or automate
decision making throughout the organization. We will
explore how these moving parts fit together strategically.
Unsupervised methods like cluster analysis, anomaly
detection, and association rules are exploratory in nature
and don’t generate a propensity score in the same way that
supervised learning methods do. So how do you take these
models and automate them in support of organizational
decision-making? This course will show you how.
This course will demonstrate a variety of examples starting
with the exploration and interpretation of candidate
models and their applications. Options for acting on results
will be explored. You will also observe how a mixture
of models including business rules, supervised models,
and unsupervised models are used together in real world
situations for various problems like insurance and fraud
detection.
You Will Learn• When to apply supervised versus unsupervised modeling
methods
• Options for inserting machine learning into the decision
making of your organization
• How to use multiple models for estimation and
classification
• Effective techniques for deploying the results of
unsupervised learning
• Interpret and monitor your models for continual
improvement
• How to creatively combine supervised and unsupervised
models for greater performance
Who is it for?Analytic Practitioners, Data Scientists, IT Professionals,
Technology Planners, Consultants, Business Analysts,
Analytic Project Leaders.
Course descriptionModel Development Introduction
• Current Trends in AI, Machine Learning and Predictive
Analytics
- Algorithms in the News: Deep Learning
- The Modeling Software Landscape
- The Rise of R and Python: The Impact on Modeling and
Deployment
- Do I Need to Know About Statistics to Build Predictive
Models?
Strategic and Tactical Considerations in Binary
Classification
• What is an Algorithm?
• Is a “Black Box” Algorithm an Option for Me?
WORKSHOPAPRIL 1 - 2, 2019
PUTTING MACHINE LEARNING TO WORKTranslating Organizational Challenges into Supervised & Unsupervised Learning Solutions
• Issues Unique to Classification Problems
- Why Classification Projects are So Common
- Why are there so many Algorithms?
Data Preparation for Supervised Models
• Data Preparation Law
• Integrate Data Subtasks
- Aggregations: Numerous Options
- Restructure: Numerous Options
- Data Construction
· Ratios and Deltas
· Date Math
· Extract Subtask
The Tasks of the Model Phase
• Optimizing Data for Different Algorithms
• Model Assessment
- Evaluate Model Results
· Check Plausibility
· Check Reliability
- Model Accuracy and Stability
- Lift and Gains Charts
• Modeling Demonstration
- Assess Model Viability
- Select Final Models
• Why Accuracy and Stability are Not Enough
• What to Look for in Model Performance
• Exercise Breakout Session
- Select Final Models
- Create & Document Modeling Plan
- Determine Readiness for Deployment
• What are Potential Deployment Challenges for Each
Candidate Model?
What is Unsupervised Learning?
• Clustering
• Association Rules
• Why most organizations utilize unsupervised
methods poorly
- Case Study #1: Finding a new opportunity
- Case Studies 2, 3, and 4: How do supervised and
unsupervised work together
- Exercise Breakout Session: Pick the right approach for
each case study
• Data Preparation for Unsupervised
- The importance of standardization
- Running an analysis directly on transactional data
• Unsupervised Algorithms:
- Hierarchical Clustering
- K-means
- Self-Organizing Maps
- K Nearest Neighbors
- Association Rules
• Interpreting Unsupervised
- Exercise Breakout Session: Which value of K is best?
- Choosing the right level of granularity
- Reporting unsupervised results
Wrap-up and Next Steps
• Supplementary Materials and Resources
• Conferences and Communities
• Get Started on a Project!
• Options for Implementation Oversight and Collaborative
Development
LOOK FOR DETAILED INFORMATION ON WWW.ADEPTEVENTS.NL/WML-EN
WORKSHOPAPRIL 1 - 2, 2019
Download the DW&BI Summit Conference-App (integrated in the BI-Platform app)
CONFERENCE-APP
DATE AND TIMEThe conference will take place on March 27 - 28, 2019 and the programme starts at 9:30 am and ends at 5:15 pm on both conference days. Registration commences at 8.30 am and we recommend that you arrive early.
VENUEThe conference will be held at the Van der Valk Hotel in Utrecht. Always check our website or conference app prior to your departure to ensure you have the exact location and directions.
Van der Valk Hotel UtrechtWinthontlaan 4-63526 KV Utrecht
Contact details hotel:Tel. (+31)30 8000800 E-mail: [email protected] hotel: www.vandervalkhotelutrecht.nl.
On the hotel website you can find a full itinerary and directions. The hotel is located on a 35 minutes drive from Amsterdam Schiphol Airport and is also easily accessible by public transport.
HOW TO REGISTERPlease register online at www.dwbisummit.com. For registering by print, please scan the completed registration form and send this to [email protected]. We will confirm your registration and invoice your company by e-mail therefore please do not omit your e-mail address when registering.
REGISTRATION FEEFull conference One day
Best rate (ends December 31, 2018)*: € 1139 € 586,50
Early registration (January 1 – February 20, 2019):
€ 1206 € 621
Regular registration (February 21 – March 27, 2019):
€ 1340 € 690
The registration fee for the workshop Putting Machine Learning to Work, when combined with attending the conference, is € 1363 and € 1226.70 when registering early.
*)Invoice will be sent in year 2019. Upon request we can send the invoice in year 2018.
Members of the the Dutch KNVI BI&A as well as DAMA are eligable for 10 percent discount on the registration fee. All prices are VAT excluded.
TEAM DISCOUNTSDiscounts are available for group bookings of two or more delegates representing the same organization made at the same time. Ten percent off for the second and third delegate and fifteen percent off for all delegates when registering four or more delegates (all delegates must be listed on the same invoice). This cannot be used in conjunction with other discounts.
PAYMENTFull payment is due prior to the conference. An invoice will be sent to you containing our full bank details including BIC and IBAN. Your payment should always include the invoice number as well as the name of your company and the delegate name.For Credit Card payment please contact our office by e-mail mentioning your phone number so that we can obtain your credit card information.
CANCELLATION POLICYCancellations must be received in writing at least three weeks before the commencement of the conference and will be subject to a € 75,- administration fee. It is regretted that cancellations received within three weeks of the conference date will be liable for the full conference fee. Substitutions by other persons can be made at any time and at no extra charge.
CANCELLATION LIABILITYIn the unlikely event of cancellation of the conference for any reason, Adept Events’ liability is limited to the return of the registration fee only. Adept Events will not reimburse delegates for any travel or hotel cancellation fees or penalties. It may be necessary, for reasons beyond the control of Adept Events, to change the content, timings, speakers, date and venue of the conference.
RECORDINGS AND PHOTOGRAPHYPlease be aware that still photography, video, and audio recording may occur at this event. By attending this event, you consent to have your image, photograph, likeness, picture, rendering, or audio recording utilized for Adept Events educational, marketing, and sales purposes. You hereby grant Adept Events the right to unrestricted use, reproduction, display, dissemination, publication, and distribution in any medium, provided that Adept Events will take measures on behalf of attendees against infringement and/or inappropriate use of your image, photograph, likeness, picture, rendering, and audio recording.
MORE INFORMATION
+31(0)172-742680
http://www.dwbisummit.com
@AdeptEventsNL | #dwbisummit
https://www.linkedin.com/company/adept-events
Visit our Business Intelligence and Data Warehousing website www.biplatform.nl and subscribe to our weekly newsletter
Download the DW&BI Summit Conference-App (integrated in the BI-Platform app)
INFORMATIONDATA WAREHOUSING & BUSINESS INTELLIGENCE SUMMIT 2019
SPONSORS AND MEDIA We thank our sponsors for supporting our conference and providing media exposure.